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Algorithm-Project

108-02 NCU CE3005-B Algorithm Final Term Project

Course

Algorithmics (演算法) 2020

Term Project

題目: 深度學習中文手寫數字辨識

輸入: 中文手寫數字資料集(dataset)

輸出: 中文手寫數字辨識準確率(accuracy)

佔分: 總成績20%

目的: 讓學生練習使用深度學習(deep learning)模型解決中文手寫數字辨識問題。

深度學習(deep learning)模型

  1. 深度神經網路(deep neural network, DNN)
  2. 捲積神經網路(convolutional neural network, CNN)
  3. 長短期記憶(long short-term memory, LSTM)神經網路
  4. 閘控遞迴單元(gated recurrent unit, GRU)神經網路

資料集說明: 資料集下載連結

資料集檔案handwrite_detect.zip為中文手寫數字資料集,包含了訓練資料集(training dataset)與測試資料集(test dataset) 訓練資料共有2450筆 測試資料共有1700筆

評分項目與規範

  1. Source code(.py)
  2. A short report (.pdf)(含有) a. 中文手寫辨識準確率(accuracy),以截圖方式呈現 b. Source code之逐行解釋

繳交方式

請將所有檔案壓縮成 .zip 後,再上傳至 LMS 作業繳交區 (上傳檔名:Term_Project_學號_姓名.zip)

繳交時間

期末考兩周後周二 20:00前截止 07/02 20:00

投影片

Google Drive Link

教學影片

  1. 機器學習環境安裝之教學影片
  2. Machine Learning 01 DNN
  3. Machine Learning 02 CNN
  4. Machine Learning 03 LSTM
  5. Machine Learning 04 GRU

備註 : 切勿互相抄襲,若發現抄襲,則以0分計算

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